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University of Illinois at Urbana-Champaign

On-Line Monitoring, Control, and Reliability of Structural Dynamical Systems

Abstract

dc:description

"Ideas for improving the efficiency of Monte Carlo simulation (MCS) is the subject of the final section. Determining the low failure probabilities of typical engineering systems is quite difficult without using millions of MCS realizations to characterize the probability distribution. Several links between some MCS variance reduction techniques and Genetic Algorithms are discussed. A simple example, incorporating Genetic Algorithm operators into MCS, is shown to estimate probabilities a couple orders of magnitude smaller than standard MCS. Several concepts for characterizing the sense of a realization's ""importance"", such as discrepancy sensitivity and phase space velocity, are examined and found to successfully quantify realization importance."

Degree

thesis:*
Name thesis:degree_name
Ph.D.
Level thesis:degree_level
Dissertation
Discipline thesis:degree_discipline
Aerospace Engineering
Grantor
University of Illinois at Urbana-Champaign
Year dc:date
2015

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Johnson, Erik Arthur
Contributors dc:contributor
  • Bergman, Lawrence A.
  • Voulgaris, Petros G.

Subjects

dc:subject × 1

Rights

Language dc:language
eng

Identifiers

dc:identifier.*
Identifier
(MiAaPQ)AAI9812643
OAI identifier oai:identifier
oai:www.ideals.illinois.edu:2142/85125

Chain of custody

source
Harvested from
University of Illinois - Urbana-Champaign
Base URL
www.ideals.illinois.edu/oai-pmh
Last updated
2026-07-22
Source record
OAI-PMH GetRecord
citation

Johnson, Erik Arthur. On-Line Monitoring, Control, and Reliability of Structural Dynamical Systems. Dissertation thesis, University of Illinois at Urbana-Champaign, 2015. http://hdl.handle.net/2142/85125